Universität Wien FIND
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053640 SE Master's Seminar (2022S)

Prüfungsimmanente Lehrveranstaltung


Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").


max. 25 Teilnehmer*innen
Sprache: Englisch



Zur Zeit sind keine Termine bekannt.


Ziele, Inhalte und Methode der Lehrveranstaltung

The aim is to conduct a data-driven project in the field of Data Science. Based on the experience gained during the implementation of the project students should learn to carry out Data Science projects on their own. The aim is also to combine previously acquired knowledge from the various courses during the study.

Art der Leistungskontrolle und erlaubte Hilfsmittel

A detailed specification of the requirements, as well as a guide and notes on the implementation of the project will be announced at the beginning of the course together with the assignment of the project topics.

Mindestanforderungen und Beurteilungsmaßstab

Prerequisites for the Masterseminar are the successful completion of:
- Introduction to Machine Learning
- Statistics for Data Science
- Mathematics for Data Science
- Optimization methods for Data Science
- Mining Massive Data
- Visual and Exploratory Analysis
- Doing Data Science
- Ethical and Legal Issues
- Data Analysis Project and Seminar


The goal is to make progress in your master thesis. You will be judged by the milestones you and your supervisor will agree upon.


Literature and further details are announced by the supervisor in the course.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 16.03.2022 09:07